Automatic Segmentation of the Human Ear Using Active Contour and GrabCut Synergy Based on the Superpixel Cluster Regions

Abstract

The ear region is a region of the human body region containing valuable biometric information that is subjected to a few physiological changes depending on the individual’s age. Manual, semi-automatic, or fully automatic segmentation of the ear region in various methods related to the use of the ear region in obtaining biometric information is an important area of research. In our study, we present an approach that applies superpixel cluster regions, active contour detection based on geodesic information, and foreground separation by graph cutting, to segregate the human ear region from the image by fully automatic segmentation from the background. Thanks to this approach in our study, the ear foreground mask is created programmatically and fully automatically from the ear image. In the experiments with the ear images data set, the reference ear mask marked by the expert was compared with the automatically created foreground mask. It has been obtained hHigh performance values were obtained, considering the similarity rates (i.e., intersection over union) based on the Jaccard index metric. Our approach has quite good performance values (in the range of 84% to 92%) for the images in this dataset. In our study, the success of the proposed synergistic approach is demonstrated both qualitatively and quantitatively with experimental results.

Keywords

• Superpixel
• Active contour
• Graph cut
• Image segmentation

Süperpiksel Küme Bölgeleri Tabanlı Aktif Çevrit Ve GrabCut Sinerjisini Kullanarak İnsan Kulağının Otomatik Bölütlenmesi

Abstract

Kulak bölgesi bireyin yaşına bağlı olarak fizyolojik bakımdan çok az değişikliğe maruz kalan değerli biyometrik bilgi içeren bir insan vücut bölgesidir. Biyometrik bilgi elde etmede kulak bölgesinin kullanımıyla ilgili çeşitli yöntemlerde kulak bölgesinin elle, yarı otomatik veya tam otomatik olarak bölütlenmesi önemli bir araştırma alanıdır. Çalışmamızda, insan kulak bölgesinin görüntüden tam otomatik olarak bölütlenerek arka plandan ayrıştırılması için süperpiksel küme bölgeleri, jeodezik bilgiye dayanan aktif çevrit tespiti ve çizge kesme yoluyla ön plan ayrıştırma işlemleri uygulayan bir yaklaşım sunulmaktadır. Çalışmamızdaki bu yaklaşım sayesinde kulak ön plan maskesi programatik ve tam otomatik biçimde kulak görüntüsünden oluşturulmaktadır. Kulak görüntüleri veri kümesi ile yapılan deneylerde uzman tarafından işaretlenen referans kulak bölgesi maskesi otomatik olarak oluşturulan ön plan maskesi ile karşılaştırılmıştır. Jaccard endeksi ölçütüne dayalı benzerlik oranları (birleşim kesişimi) dikkate alındığında yüksek başarım değerleri elde edilmiştir. Yaklaşımımız bu veri kümesindeki görüntüler için %84 ilâ %92 aralığında oldukça iyi başarım değerlerine sahiptir. Çalışmamızda, önerilen sinerjik yaklaşımın başarımı hem niteliksel hem de niceliksel olarak deneysel sonuçlarla ortaya konulmaktadır..

Keywords

• Süperpiksel
• Aktif çevrit
• Çizge kesme
• Görüntü bölütleme

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